n8n vs Make vs Zapier: Choosing Your Automation Platform

When it comes to connecting your AI systems to the rest of your business tools, you've got three major players: n8n, Make (formerly Integromat), and Zapier. I've built workflows on all three platforms, and each has its strengths. Let me break down what I've learned so you can pick the right one for your needs.

The 30-Second Summary

Zapier is the easiest to use but most expensive. Make gives you powerful visual automation at mid-tier pricing. n8n is the most flexible and cost-effective if you're willing to self-host. That's the oversimplified version—let's get into the details.

Pricing: The Real Differentiator

This is probably the biggest factor for most teams, so let's start here. The pricing models are completely different, and your costs can vary by 10x depending on which platform you choose.

Here's what this looks like in practice: I have a client running about 50,000 workflow executions per month (processing customer support tickets with AI, syncing data between systems, that kind of thing). On Zapier, that would cost them around $400-500/month. On Make, it's about $50/month. On self-hosted n8n, it's basically free beyond the server costs (~$20/month).

That's a massive difference, and it's why I usually steer clients toward Make or n8n unless they really need Zapier's simplicity.

User Interface and Learning Curve

Zapier wins hands-down for ease of use. The interface is dead simple—you pick a trigger, add some actions, maybe add a filter or two. My non-technical clients can build basic Zaps without my help. It's that straightforward.

Make has a visual flow-based interface that's more powerful but slightly steeper learning curve. You connect nodes on a canvas, and you can see the data flowing through your workflow. It's actually pretty intuitive once you spend 30 minutes with it. The visual debugger is excellent—you can see exactly what data each step produces.

n8n is similar to Make in terms of the visual interface, but it assumes a bit more technical knowledge. You'll be writing JavaScript expressions for data transformations, working with JSON directly, and dealing with API authentication. If you've got a technical team, it's not a problem. If you're trying to empower your marketing team to build automations, it might be too much.

AI and LLM Integration

This is where things get interesting for my use cases. All three platforms can connect to OpenAI, Claude, and other LLM APIs, but the implementation quality varies.

Zapier has official integrations with ChatGPT and a few others. They work fine for simple prompts, but you're limited to what Zapier exposes in their UI. Want to use advanced features like function calling or vision models? You'll need to use webhooks and custom code, which defeats the purpose of using Zapier.

Make has good OpenAI integration and supports most major AI APIs. The HTTP module is powerful enough to call any API, and you can parse responses however you need. I've built some complex RAG workflows in Make that pull from vector databases, format prompts, call Claude, and parse the results. It works well.

n8n is the clear winner for AI workflows. They have first-class nodes for OpenAI, Anthropic, Cohere, HuggingFace, and more. You can build multi-step AI workflows that chain together different models, use embeddings, query vector databases—basically anything you can imagine. Plus since it's open source, people build custom nodes for new AI services all the time.

# Example n8n workflow for AI-powered customer support
1. Trigger: New Zendesk ticket
2. HTTP Request: Query Pinecone for similar past tickets
3. OpenAI Node: Generate response using RAG context
4. IF Node: Check if confidence > 0.8
5a. (High confidence) Post reply to Zendesk
5b. (Low confidence) Assign to human agent
6. Slack: Notify support team

I built that exact workflow for a SaaS company, and it handles about 40% of their support tickets automatically. Would've been much harder to build in Zapier.

Technical Capabilities

Error Handling: All three platforms retry failed steps, but they handle it differently. Zapier is the simplest—basic retries and email notifications. Make has more sophisticated error handling with custom error paths. n8n gives you complete control with try/catch logic and custom error workflows.

Data Transformation: Zapier uses a formatter tool that covers basic transformations. Make has a powerful set of functions and a formula syntax similar to Excel. n8n lets you write JavaScript directly, which means you can do literally anything.

Branching and Logic: This is where Zapier really falls behind. You can add filters and paths, but complex conditional logic gets messy fast. Make handles this beautifully with routers and filters. n8n is similarly powerful with IF nodes and switches.

Available Integrations

Zapier has the most integrations by far—over 5,000 apps. If you need to connect to some obscure SaaS tool, Zapier probably has it. Make has about 1,500 integrations, which covers most popular business tools. n8n has fewer pre-built integrations (maybe 400), but since you can make HTTP requests to any API, it doesn't really matter if you're technical.

For AI-specific tools, n8n actually has better coverage. They have nodes for Pinecone, Weaviate, Qdrant, LangChain, and various LLM providers that Zapier doesn't support natively.

Self-Hosting vs. Cloud

This is n8n's killer feature. You can run it on your own infrastructure, which means:

• No limits on execution volume (beyond your server capacity)
• Complete data privacy and control
• Ability to access internal systems behind firewalls
• Predictable costs regardless of usage

For one enterprise client, we deployed n8n on their AWS infrastructure and connected it to internal databases and APIs that weren't accessible from the internet. That simply wouldn't have been possible with Zapier or Make's cloud offerings.

Make recently introduced Make On-Premises, but it's enterprise-only and expensive. Zapier doesn't offer self-hosting at all.

Debugging and Monitoring

When workflows break (and they will), you need good debugging tools. Make's visual debugger is excellent—you can see the exact data at each step and replay executions. n8n has a similar execution viewer that's very helpful. Zapier's history view is more basic but gets the job done for simple workflows.

For monitoring, Zapier sends email alerts when things fail. Make has a notification system and task history. n8n can send webhooks to your monitoring tools (PagerDuty, Slack, whatever), and since you control the infra, you can set up custom logging and alerting.

Version Control and CI/CD

If you care about treating your workflows as code (and you should for production systems), n8n is the only real option. Workflows are stored as JSON files that you can commit to Git, review in pull requests, and deploy through CI/CD pipelines.

Make has some version history, but it's not great. Zapier has basically nothing—if you want to track changes, you're taking screenshots or keeping a changelog manually.

Performance and Reliability

All three platforms are generally reliable, but I've seen differences in execution speed. Zapier can be slow—sometimes there's a noticable delay between trigger and action, especially on lower-tier plans. Make is faster, with most executions completing in seconds. n8n performance depends on your infrastructure, but it's typically very fast since you control the resources.

For high-volume workflows, n8n definitely wins. I've run workflows processing thousands of items per minute without issues. Try to do that on Zapier and you'll hit rate limits and rack up massive costs.

When to Choose Zapier

Choose Zapier if:

• You need the simplest possible interface for non-technical users
• You're using niche SaaS tools that only Zapier supports
• Your workflow volume is low (under 10K tasks/month)
• You don't need complex logic or branching
• Budget isn't a primary concern
• You want the most mature platform with tons of documentation

When to Choose Make

Choose Make if:

• You want a good balance of power and ease of use
• You need visual workflow building but with advanced logic
• Your volume is moderate to high (10K-100K+ ops/month)
• You want better pricing than Zapier but don't want to self-host
• You need good AI/LLM integration without getting too technical
• The visual debugger appeals to you

When to Choose n8n

Choose n8n if:

• You have technical team members who can manage infrastructure
• You need to self-host for security, compliance, or cost reasons
• You're building complex AI workflows with RAG, embeddings, etc.
• You want version control and CI/CD for your workflows
• Your execution volume is very high (100K+ per month)
• You need to access internal systems behind firewalls
• You want complete control and customization

My Recommendation

For most teams starting out with simple automations, Make is the sweet spot. It's powerful enough to grow with you, priced reasonably, and doesn't require infrastructure management. The learning curve is gentle enough that your team can pick it up quickly.

If you're building AI-heavy workflows and have technical resources, go straight to n8n. The self-hosting might seem daunting, but it's really not that hard—you can get it running on a $20/month server in an afternoon. The flexibility and cost savings are worth it.

I only recommend Zapier for teams that are completely non-technical and have simple automation needs. Even then, I'd suggest starting with Make and seeing how it goes.

Migration Considerations

If you're already using one platform and considering switching, the migration path varies. Going from Zapier to Make is relatively straightforward—the concepts are similar enough that you can rebuild workflows pretty quickly. Going to n8n takes more effort since you'll need to set up infrastructure and potentially rewrite some logic.

I've migrated several clients from Zapier to n8n, and it typically takes 1-2 weeks for a dozen or so workflows. The ROI is fast if you're running high volumes.

Final Thoughts

The automation platform landscape has really matured. All three of these tools are solid choices that'll get the job done. The right pick depends on your team's technical capabilities, workflow complexity, execution volume, and budget.

For AI integration specifically, n8n has the edge. For ease of use, Zapier wins. For the best balance of features and pricing, Make is hard to beat.

Whatever you choose, the important thing is to actually build the automations. I've seen too many teams spend weeks debating platforms when they could've just started building and figured out what they actually need. Start simple, validate that automation solves your problem, then optimize from there.

And if you need help building those workflows or integrating AI into your automation stack, that's exactly what I do. Feel free to reach out.